The graph database (wiki) is now a buzzword, as the technology is growing fast and businesses can’t afford to ignore this as due to the immense benefits, this technology offers it is rightly being predicted as the future of DBMS (Database Management Systems). Some important graph database examples are Neo 4J, Amazon Neptune, and Orient DB. For all inquisitive readers who are keen to know what a graph database is and what are its major benefits, this article is an effort to provide requisite information:
What Is A Graph Database?
Simply defined, it is a collection of nodes (entities) and edges (relationships). The graph database, unlike other databases, store relationships inherently or by default. This implies that in the graph database, relationships are treated as equally important (or rather more important) than data itself. Nodes are assigned with any number of key-value pairs or attributes which are called properties. Edges or relationships carry directed and named relationships (which are semantically relevant connections). The example of the relationship between two nodes is an employee working for a company. For having a better understanding of what a graph database is, see the graphical illustration below:
Entities and Their Relationships-Twitter Example
Each line shows, which two Persons follow each other.
The above illustration consists of a very small portion of Twitter that has millions of inter-connected account holders. We have chosen only three users, Julia, Robert, and Smith. These are nodes (entities-persons in this illustration). In a very simplified manner, the other part of the graph database i.e. relationships is shown through arrows showing how these users are connected with each other. The illustration shows that all follow each other, there is only one exception; Robert does not follow Smith.
This is a world of inter-connectivity; we are living in today. Twitter, Facebook, Instagram, and other social media platforms explain well how much connected the nodes/entities (persons for example) are with multiple nodes through edges or relationships.
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Why Does an Enterprise Need Graph Database?
Why graph database is so quickly evolving as a mainstream database management system? What is so charming about it that giants like Google, Facebook, Twitter, and IBM are its adaptors? Today’s business enterprises, amidst stiff competition, require speedy and meaningful information in order to take timely decisions. They want to use a database for problem-solving, customer analytics, real-time updates, and faster queries and serves all this and many more purposes effectively. Let’s check out some significant advantages for enterprises:
a. Meaningful MIS:
It is built on interlinked information that is factual. Thus, it represents knowledge. It is therefore very easy for humans and machines to interpret the information stored in a graph database, unlike a traditional relational database. It is due to this factor that graph databases are so effective in providing knowledgeable responses for queries.
b. High Performance:
c. Benefits for Retail Business:
- Same day delivery services: The surge in consumer data because of the rising of online shopping and social media, have outpaced the capacity of relational databases. Now retail businesses are in a dire need to have the fastest possible delivery system. Graph database efficiently serves this purpose. To bolster its same-day delivery system; eBay is already using the tool.
- Monitoring online shopping behavior: Walmart is using a graph database to collect and analyze peer-to-peer information about consumer’s preferences about products and desired price points.
- Know your customer through Analytics: With strong analytics of graph database, businesses are gaining great insight into consumer behavior and preferences. This helps those in devising effective marketing strategies. Since graph databases also provide useful information about product pricing, they can launch effective promo coupons or discounts and deals. Graphs also provide a wealth of information about browsing and purchasing history of consumers, thus enabling to the target audience for coupon marketing. For instance, based on information obtained from the graph database, eCommerce brands can send personalized coupons to cart abandoners. For example, Vimeo which is a web video store to help people create, discover, share and sell videos, uses analytics intelligently to launch their Vimeo coupons in boosting its sales revenue. It consistently offers discount coupons for new subscribers to improve it’s brand’s image and customer base.
d. Supply Chain Management:
The impressive performance of graph database in the area of supply chain management is the result of the following factors:
- Graph database has enormous scalability and can grow and adapt to any size. No matter how large a supply chain network is, the graph database can handle it because of its capability to add as many nodes as required.
- Graphs can manage any network no matter how complex that is. There are global networks of suppliers for certain products, spread in many countries, which in turn have their own suppliers. Even in these complex networks, graph database will perform excellently because of their inherent property of storing nodes with scores of interconnections with edges.
- The graph databases have the capability to search swiftly and strongly across vast data sets and this robust searching ability makes it competent to search products, suppliers, manufacturers and facilities across complex supply chain networks.
Supply Chain Management Solutions-Relational VS Graph database
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Major Advantages of Graph Database:
Graph database advantages are too many. Here I will discuss some of the most significant benefits:
a. Speed:
b. Transformation:
The BBC has used the graph database “Ontotext” to integrate its most precious data resources. This integration has immensely benefited the financial industry where, graph database along with other semantic technologies, has provided innovative solutions in the areas of fraud detection and compliance management by bringing in transformation in existing systems.
c. Easy Data Analysis:
d. Enhanced Flexibility:
The flexibility of the graph database is one of the significant factors, responsible for its surging popularity in recent years.
Comparison Between Relational, Key-Value and Graph Database:
I will compare relational and key-value databases with graph database to highlight major differences and relative advantages.
Structure:
Transactions:
Analytics:
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Wrap Up:
The growth of the graph database in leaps and bounds and its adoption by big brands is clearly indicating its future. It is sure to evolve into a great platform for businesses, especially eCommerce for having an in-depth all-round and holistic view about their performance. From compliance management to fraud detection and supply chain to digital marketing, its benefits are so great that it will be really difficult for enterprises to ignore it.
This article is written by Jake James from EmuCoupon.com. He is a blogger, traveler, and a deep thinker. Jake loves to write on all topics especially technical, fashion, traveling and so on. Writing is his passion and therefore, he read a lot too to get ideas and to explore different topics.